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   "source": [
    "#Udemy Course >> LLM Engineering: Master AI and LLMs\n",
    "#Student: Jay\n",
    "#Date: Apr 20, 2025\n",
    "#Home work: Day1 - Summmarize website using local LLama\n",
    "\n",
    "import os\n",
    "import requests\n",
    "from dotenv import load_dotenv\n",
    "from bs4 import BeautifulSoup\n",
    "from IPython.display import Markdown, display\n",
    "from openai import OpenAI"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "01e91579-7e32-4c4d-9cc9-c06d13c16209",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Constants\n",
    "\n",
    "OLLAMA_API = \"http://localhost:11434/api/chat\"\n",
    "HEADERS = {\"Content-Type\": \"application/json\"}\n",
    "MODEL = \"llama3.2\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "8d780fba-868c-4216-88f5-1e3ca5ad43ed",
   "metadata": {},
   "outputs": [],
   "source": [
    "# A class to represent a Webpage\n",
    "# If you're not familiar with Classes, check out the \"Intermediate Python\" notebook\n",
    "\n",
    "# Some websites need you to use proper headers when fetching them:\n",
    "headers = {\n",
    " \"User-Agent\": \"Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/117.0.0.0 Safari/537.36\"\n",
    "}\n",
    "\n",
    "class Website:\n",
    "\n",
    "    def __init__(self, url):\n",
    "        \"\"\"\n",
    "        Create this Website object from the given url using the BeautifulSoup library\n",
    "        \"\"\"\n",
    "        self.url = url\n",
    "        response = requests.get(url, headers=headers)\n",
    "        soup = BeautifulSoup(response.content, 'html.parser')\n",
    "        self.title = soup.title.string if soup.title else \"No title found\"\n",
    "        for irrelevant in soup.body([\"script\", \"style\", \"img\", \"input\"]):\n",
    "            irrelevant.decompose()\n",
    "        self.text = soup.body.get_text(separator=\"\\n\", strip=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "839b645f-90ee-434d-b0bd-1cb4e574a8de",
   "metadata": {},
   "outputs": [],
   "source": [
    "system_prompt = \"You are an assistant that analyzes the contents of a website \\\n",
    "and provides a short summary, ignoring text that might be navigation related. \\\n",
    "Respond in markdown.\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "ef2453e8-3eca-4f6d-8ccf-9e5274b589a7",
   "metadata": {},
   "outputs": [],
   "source": [
    "def user_prompt_for(website):\n",
    "    user_prompt = f\"You are looking at a website titled {website.title}\"\n",
    "    user_prompt += \"\\nThe contents of this website is as follows; \\\n",
    "please provide a short summary of this website in markdown. \\\n",
    "If it includes news or announcements, then summarize these too.\\n\\n\"\n",
    "    user_prompt += website.text\n",
    "    return user_prompt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "6ec397d5-e9b0-411d-8bdb-66605273cb11",
   "metadata": {},
   "outputs": [],
   "source": [
    "messages = [\n",
    "    {\"role\": \"system\", \"content\": \"You are a snarky assistant\"},\n",
    "    {\"role\": \"user\", \"content\": \"What is 2 + 2?\"}\n",
    "]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "76aed9eb-a085-4687-859d-817c771156fa",
   "metadata": {},
   "outputs": [],
   "source": [
    "def messages_for(website):\n",
    "    return [\n",
    "        {\"role\": \"system\", \"content\": system_prompt},\n",
    "        {\"role\": \"user\", \"content\": user_prompt_for(website)}\n",
    "    ]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "26de4682-cf4f-4b7e-8cb2-049f7f46b758",
   "metadata": {},
   "outputs": [],
   "source": [
    "def summarize(url):\n",
    "    website = Website(url)\n",
    "    ollama_via_openai = OpenAI(base_url='http://localhost:11434/v1', api_key='ollama')\n",
    "\n",
    "    response = ollama_via_openai.chat.completions.create(\n",
    "        model=MODEL,\n",
    "        messages=messages_for(website)   \n",
    "    )\n",
    "    return response.choices[0].message.content"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "16b2532a-d44c-4903-83ec-0b828a2d1b92",
   "metadata": {},
   "outputs": [],
   "source": [
    "def display_summary(url):\n",
    "    summary = summarize(url)\n",
    "    display(Markdown(summary))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "86af4905-5d5c-47c9-b9b2-27257452ff94",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/markdown": [
       "**Anthropic Website Summary**\n",
       "=====================================\n",
       "\n",
       "### Mission and Values\n",
       "\n",
       "Anthropic's mission is to build AI that serves humanity's long-term well-being. They focus on designing powerful technologies with human benefit at their foundation, aiming to demonstrate responsible AI development in practice.\n",
       "\n",
       "### Notable Releases\n",
       "\n",
       "#### 2025\n",
       "\n",
       "* **Claude 3.7 Sonnet**: Anthropic's most intelligent AI model, now available.\n",
       "* Recent news articles:\n",
       "\t+ \"Tracing the thoughts of a large language model: Interpretability\"\n",
       "\t+ \"Anthropic Economic Index: Societal Impacts\"\n",
       "\n",
       "### Products and Solutions\n",
       "\n",
       "* **Claude**: A suite of AI tools for building applications and custom experiences with human benefit in mind.\n",
       "* **Claude Overview**, **API Platform**, and various other products, including:\n",
       "\t+ **Claude 3.5 Haiku**\n",
       "\t+ **Claude 3 Opus**\n",
       "\n",
       "### Research and Commitments\n",
       "\n",
       "* The Anthropic Academy: A learning platform for developers to build AI solutions with Claude.\n",
       "* Responsible scaling policy and alignment science initiatives.\n",
       "\n",
       "### News Section (Selection)**\n",
       "\n",
       "Anthropic's recent news articles:\n",
       "* \"Claude extended thinking\"\n",
       "* \"Alignment faking in large language models\"\n",
       "\n",
       "### Company Information\n",
       "\n",
       "For more information on Anthropic, including company, careers, and help resources, follow the provided links."
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
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   ],
   "source": [
    "display_summary(\"https://anthropic.com\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a5151062-614e-44ff-b341-d3f64e28aa93",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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